{"id":"W2970132222","doi":"10.1111/bcp.14104","title":"Impact of medicines regulatory risk communications in the UK on prescribing and clinical outcomes: Systematic review, time series analysis and meta‐analysis","year":2019,"lang":"en","type":"review","venue":"British Journal of Clinical Pharmacology","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Confidence interval; Medicine; Relative risk; Meta-analysis; Interrupted Time Series Analysis; Family medicine; Internal medicine; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.02916127,0.002503224,0.01709961,0.007084504,0.0005490127,0.003689277,0.001777812,0.002087446,0.002391499],"category_scores_gemma":[0.09204119,0.001543954,0.03964629,0.008473053,0.0008758754,0.002301326,0.00173925,0.002142105,0.0002464174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003731155,"about_ca_system_score_gemma":0.004914569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007792583,"about_ca_topic_score_gemma":0.01354609,"domain_scores_codex":[0.9686262,0.01592397,0.00906817,0.002467621,0.00337281,0.000541154],"domain_scores_gemma":[0.9186488,0.0610175,0.01396635,0.001937969,0.004022947,0.0004065071],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.002409399,0.00003493014,0.005515902,0.3399892,0.6365104,0.0001016867,0.00009775291,0.0006649087,0.0001483009,0.0001111065,0.0005522284,0.01386424],"study_design_scores_gemma":[0.0006926773,0.0003938835,0.007109783,0.03217889,0.9571815,0.0001216725,0.00006218703,0.0003089878,0.0001840679,0.0001768792,0.001557032,0.00003242876],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.006728893,0.9909642,0.0007042212,0.0002267379,0.0001697706,0.0003579215,0.0005947843,0.00002771497,0.0002257559],"genre_scores_gemma":[0.2705339,0.7211311,0.003222613,0.0009951395,0.0003525,0.002193078,0.001138432,0.00005103383,0.0003820592],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9829004,"threshold_uncertainty_score":0.1542213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.342949846412742,"score_gpt":0.5975179890362511,"score_spread":0.2545681426235091,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}